| Title | Uncovering The Circular Potential: Estimating Material Flows For Building Systems Components Reuse In The Swiss Built Environment |
|---|---|
| ID_Doc | 27125 |
| Authors | Xiong, SY; Escamilla, EZ; Habert, G |
| Title | Uncovering The Circular Potential: Estimating Material Flows For Building Systems Components Reuse In The Swiss Built Environment |
| Year | 2024 |
| Published | |
| Abstract | The construction industry plays a critical role in global resource consumption and greenhouse gas emissions, highlighting the urgent need for sustainable development practices. However, a key challenge in this area is the lack of effective models for resource use that align with circular economy principles. This gap hinders efforts to achieve sustainable resource management, especially in the face of increasing urbanization and material demand. To address this issue, our study presents a Parametric Predictive Model (PPM) to improve resource efficiency, specifically targeting the often-underestimated building systems. The model takes a bottom-up approach, utilizing local databases to accurately assess material stocks of building systems, thereby improving the granularity of data on material composition. Using advanced machine learning algorithms, the model processes both categorical and non-categorical data. The output, an enriched comprehensive database can support more informed decision making in sustainable resource recovery and allocation, but also contribute to the broader goals of reducing waste and promoting resource efficiency in the built environment. |
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